A regular contributor to EDSTAT-L (KW) asked about how to handle a bad peer review of an article that a colleague had submitted. The reviewer appeared to get the definitions of positive and negative skewness backwards.
That’s a point where I encourage people to be charitable. Why not assume that the reviewer just got momentarily confused about positive and negative skewness. I still get my left foot and right foot confused during dance lessons.
The reviewer also suggested that analysis of transformed data was a “data manipulation trick” and requested that the analysis be done on the original untransformed data.
If a reviewer suggests a minor change in the data analysis, and that’s all it takes to get the paper published, I generally encourage people to give in on this point. Arguing over a minor point isn’t worth it in the long run. Unless you have a really strong reason to keep the analysis unchanged, re-run the analysis on the untransformed data. It won’t take more than a few minutes and it virtually guarantees publication.
This reviewer did use rather harsh language and it a bit of a nit-picker, so it’s hard not to react defensively. But I think the wisest course is to save your ammunition for the truly important battles. When a reviewer says “I don’t like how you analyzed the data” I try to be grateful that they didn’t say “This data is so awful that no data analysis could salvage it.”
(Update: November 24, 2006) My response and other responses are summarized at
- Ignorant Experts. Wuensch K. Last viewed on 2006-11-24. core.ecu.edu/psyc/wuenschk/docs30/IgnorantExperts.htm